SCCT 2022: Defining the Future of Cardiovascular CT

Last week, our team at Cleerly had the opportunity to take part in a gathering of impassioned cardiac computed tomography (CT) leaders at the Society of Cardiovascular Computed Tomography (SCCT) Annual Scientific Meeting in Las Vegas. As the former president of the SCCT, I had the privilege of serving as chair for the Annual Scientific Sessions meeting for five years and have seen first-hand the invaluable insights this event brings to organizations, new practitioners and experienced providers alike. I want to thank the SCCT for their leadership in continuing to bring together our community as we advocate for research, education and clinical excellence to define new standards for cardiovascular care.

As a sponsor of SCCT, we hope that Cleerly had a marked presence across this year's event. My colleague James Earls, M.D., FSCCT, and I had the privilege to lead a workshop on artificial intelligence (AI) and machine learning, giving event delegates hands-on experience with the latest technology developments in the field that have the potential to impact the future of cardiovascular medicine and cardiovascular CT.

While at the conference, we announced that our CONFIRM2 clinical trial registry has already enrolled 11,000 patients, and is set to evolve into the largest cardiovascular phenotype outcomes study ever performed. CONFIRM2 is designed to evaluate associations between coronary computed tomography angiography (CCTA) imaging findings and clinical presentation and their ability to predict mortality and major adverse cardiac events in patients with coronary artery disease (CAD). Through it, a global consortium of leaders in cardiovascular CT will introduce new concepts in vascular biology that will hone in on the goal of truly personalizing cardiovascular care.

The CONFIRM2 clinical study is just one of the many ways our team is attempting to provide valuable knowledge for the cardiology field at large to better understand how to prevent heart attacks through non-invasive, preventive imaging. At SCCT, we also presented eight abstracts in partnership with our esteemed collaborators, demonstrating our ongoing research that we hope will impact how we screen, treat, diagnose and prevent heart disease in the years to come:

Predicting Ischemia Using AI-QCT vs. Functional Testing

• This study compares the performance of artificial intelligence quantitative computed tomography (AI-QCT) to non-invasive FFR (FFRCT) and myocardial perfusion imaging (MPI) for identifying functional ischemia. AI-QCT measures were found to more accurately predict coronary ischemia than FFRCT or MPI, when compared to an invasive FFR reference standard. This data supports the use of AI-QCT for the non-invasive assessment of functional ischemia and, presented by Dr. Rebecca Jonas, was awarded best abstract in the Canon Young Investigators Award competition.

Opportunities for Enhanced Preventive Therapies Through AI-QCT: A Multicenter Study

• AI-QCT now allows for rapid, accurate assessment of coronary vessel morphology, stenosis and atherosclerosis evaluation through artificial intelligence. In this study, AI-QCT identified significantly more patients with atherosclerosis, at the traditionally lower risk spectrum, who may benefit from preventive therapies when compared to current clinical practice approaches.

Association Between Coronary Artery Calcium and Calcified Plaque Volume and Their Ability to Predict Obstructive Coronary Artery Disease: CLARIFY Registry

• While the Agatston coronary artery calcium (CAC) score is a strong predictor of mortality, the relationship between the Agatston CAC score and calcified plaque volume (CPV) is not well understood. This study elucidated the relation between CAC and CPV, and highlighted the added value of CPV over CAC in predicting obstructive CAD.

AI-QCT Guided by Artificial Intelligence: Novel Thresholds to Predict Cardiac Outcomes

• Using AI-QCT, we evaluated the efficacy of standardized plaque thresholds and ranges to predict major adverse cardiovascular events (MACE). In this study, AI-QCT identified plaque volume thresholds identified stepwise risk of MACE, suggesting its importance in improving identification of at-risk patients independent of coronary % diameter stenosis evaluation.

Artificial Intelligence Guided AI-QCT: Gatekeeper for Invasive Angiography?

• This study compared AI-QCT to CCTA reads in selective referral to invasive coronary angiography (ICA) as well as MACE. In stable patients eligible for ICA, use of selective referral with AI-QCT may allow for 87-95% reduction in unnecessary ICA referral of individuals who may not benefit from the invasive procedures.

As we look toward the future of our field, seminal conferences like SCCT are instrumental to change the current standard of cardiovascular care and disseminate new knowledge of vascular biology and coronary atherosclerosis. Driving this change will be a significant undertaking, but we also see amazing opportunities ahead to redefine our approach to cardiovascular evaluation and treatment through risk identification, quantification and preventive care – enabling better outcomes and healthier, more knowledgeable and satisfied patients. The sooner we can enact this bold shift in our care paradigm, the closer we will be to ending the world’s #1 public health epidemic.

A large thanks to all of those individuals who contributed to the massive success of this year’s SCCT Scientific Sessions. We look forward to participating again next year!

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